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Record W4417364327 · doi:10.5604/01.3001.0055.4368

Influence of interface notch geometry on the tensile behaviour of FGF-printed parts

2025· article· en· W4417364327 on OpenAlexaff
Maryam Shokrollahi, Adam W. Smith, Martine Dubé, Ilyass Tabiai

Bibliographic record

VenueJournal of Achievements of Materials and Manufacturing Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsUltimate tensile strengthDigital image correlationThermoplasticTensile strainLayer (electronics)Tensile testingInterface (matter)Indentation

Abstract

fetched live from OpenAlex

<ns3:p>The paper investigates the influence of interface notches ‒ formed due to extrudate geometry ‒ on the tensile performance of parts manufactured by fused granular fabrication (FGF). Although FGF enables fast, cost-effective, large-scale printing with thermoplastic pellets, its adoption in industry remains limited, mainly due to poor mechanical performance. Interface notches have been identified as a key contributor to this limitation. The study investigates the effect of layer height on notch severity and its impact on the tensile behaviour of PETG samples, to improve understanding and guide process optimisation.Single-extrudate-thick PETG walls were printed at two different layer heights (3 mm and 4.5 mm) using a large-scale pellet-fed 3D printer. Tensile specimens were extracted from these walls and tested using digital image correlation (DIC) to map full-field strain. Interface notch geometry was characterised through optical microscopy and image analysis, focusing on key parameters including notch depth, angle, and root radius. The geometric features were then correlated with the tensile properties and localised strain distribution observed during loading.Increasing the layer height resulted in deeper, sharper interface notches that raised the strain concentration factor and caused more premature failure. The 4.5 mm layer height sample showed a 31% reduction in ultimate stress and a 29% decrease in strain at break compared to the 3 mm sample. DIC analysis confirmed that the strain localised at the notch roots, highlighting the impact of severe notches on tensile performance.Future studies could expand on this work by exploring a wider range of layer heights, nozzle sizes, materials, and interfacial healing conditions. Quantifying the evolution of notch geometry across multiple process variables could help establish predictive models for failure.Understanding the role of notch geometry in FGF-printed parts helps inform optimal printing strategies for improving part strength and reliability. Findings can guide design choices in the structural applications of large-format printing, where the extrudate shape has a significant influence on performance.The paper highlights the often overlooked role of interface notch geometry as a key driver of failure in FGF-printed structures. By combining DIC and quantitative notch characterisation, it offers new insights into the geometric mechanisms behind anisotropy and strength reduction in material extrusion additive manufacturing.</ns3:p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.217
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

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